Network capacity planning is a process of measuring a networks ability to serve content to its users at an acceptable speed. The process involves measuring the number of active users and by how much demand each user places on the server, and then calculating the computing resources that are necessary to support the usage levels.
Two key elements of network capacity performance are bandwidth and latency. Bandwidth is just one element of what a person perceives as the speed of a network. Another element of speed, closely related to bandwidth, is latency. Latency refers generally to delays in processing network data, of which there are several kinds. Latency and bandwidth are related to each other. Whereas theoretical peak bandwidth is fixed, actual or effective bandwidth varies and can be affected by high latencies. Too much latency in too short a time period can create a bottleneck that prevents data from “filling the pipe,” thus decreasing effective bandwidth. Businesses use the term Quality of Service (QoS) to refer to measuring and maintaining consistent performance on a network by managing both bandwidth and latency.
Prior network capacity systems, either analytical and/or discreet event simulation tools, import a limited amount of live application traffic patterns to drive a model of user's network configurations. To validate a pre-existing network traffic model, a network analyst needs to compare two simulation runs and spend considerable time adjusting the pre-existing simulated traffic patterns to match the network load of the imported live traffic patterns. The effort to perform this task is challenging and is not usually attempted. Importing production traffic patterns, using trace files, is limited with respect to time coverage. It would be very difficult to import a series of trace files covering all the peak hours of traffic activity over-several weeks. It would also very difficult to identify and compare the simulated traffic with real production traffic in order to adjust the simulated patterns to allow for future simulation runs that can predict what affect new clients will have on network bandwidth requirements. Hence, using these tools for multiple applications is very time consuming, expensive and not usable by average individuals typically in the position to do network sizing and performance estimates.
Accordingly, there is a need for a system, method, computer product, and user interface supporting estimating network load used by multiple concurrently operating executable software applications.